Abstract

Objective: This study critically examines legal frameworks governing artificial intelligence (AI) decision-making, focusing on accountability, transparency, liability, and the protection of fundamental human rights. It evaluates the adequacy of existing legislation, compares jurisdictional approaches, and proposes an integrated governance model for AI systems.

Method: A doctrinal legal research methodology is employed, complemented by comparative and analytical approaches. Primary sources include EU and international AI legislation, GDPR provisions, and human rights instruments. Secondary sources comprise peer-reviewed scholarship, regulatory reports, and institutional analyses.

Findings: The study finds that AI regulation is evolving toward a risk-based, lifecycle-oriented, and rights-integrated model. Key developments include preventive compliance obligations, integration of fundamental rights, and multi-layered enforcement mechanisms. Persistent challenges remain in operationalising accountability, transparency, human oversight, and mitigation of structural bias.

Value: The study provides a consolidated analysis of AI governance, offering insights for policymakers, regulators, and legal practitioners. By mapping doctrinal gaps and proposing coherent regulatory strategies, it supports the design of legally robust, socially responsible, and globally harmonised AI frameworks.